|
|
Absolute deviation, 绝对离差$ b/ W! [7 E4 o# x' I. F. B- _
Absolute number, 绝对数
]- M* Q" P8 L! j; C# }: S; aAbsolute residuals, 绝对残差
% {- \1 F9 G1 qAcceleration array, 加速度立体阵
" E3 c) x6 y$ d3 l1 Y* P6 RAcceleration in an arbitrary direction, 任意方向上的加速度
9 ]* k! p4 s g/ P1 iAcceleration normal, 法向加速度
+ r0 }3 M& @! b% S1 DAcceleration space dimension, 加速度空间的维数6 H2 Q( M' F9 T/ S" W0 @$ F- Z" U
Acceleration tangential, 切向加速度4 j* P3 S4 ^6 g0 _0 a
Acceleration vector, 加速度向量
3 @8 d. F9 f8 N. [8 kAcceptable hypothesis, 可接受假设
1 E5 K& ?' R c% s3 [) ~Accumulation, 累积, W# _6 m& V/ S: R @ R
Accuracy, 准确度( Q# p/ x0 w& [) J0 g
Actual frequency, 实际频数1 h) {. S8 `7 @7 {+ k+ [
Adaptive estimator, 自适应估计量
! g W2 ^2 D2 T/ K% S M4 bAddition, 相加5 H5 ]9 e* a+ r
Addition theorem, 加法定理
4 B4 D/ G1 t! v- n7 d5 \" |& W3 nAdditivity, 可加性
% F; @' Z2 l6 m$ I1 ^7 HAdjusted rate, 调整率
( l; b" _9 I# E3 m0 `' f, y ]Adjusted value, 校正值8 u6 D3 W9 E6 {! Z$ j
Admissible error, 容许误差2 K" j" z: f; @5 S
Aggregation, 聚集性
* u$ Q2 r V- q. Q' E- F$ ]Alternative hypothesis, 备择假设9 X. e7 J* S* w
Among groups, 组间0 u; R& M( x3 ^9 q' V: d
Amounts, 总量
8 k7 F; s9 _' ]$ z. VAnalysis of correlation, 相关分析
, x4 \3 J# R j" @7 q: v' k+ WAnalysis of covariance, 协方差分析0 r% X& h, i) |9 `" x) D
Analysis of regression, 回归分析
' j W6 M9 V$ x$ H% e- _+ B) C4 CAnalysis of time series, 时间序列分析
# Q) ~; F: Y" F6 g% jAnalysis of variance, 方差分析: q3 [, f9 `3 D5 h6 O2 y0 p% N; B
Angular transformation, 角转换
; v; p& u- {% m* o0 eANOVA (analysis of variance), 方差分析
- O- S6 ?2 D0 j. ~' OANOVA Models, 方差分析模型6 j: K6 A6 j& P
Arcing, 弧/弧旋1 B q! `" ?" k" A- r
Arcsine transformation, 反正弦变换3 u( L/ x% q; H. d0 z
Area under the curve, 曲线面积) z* x. d' U- K, s9 Z3 W
AREG , 评估从一个时间点到下一个时间点回归相关时的误差 8 \+ Q7 a5 e0 L
ARIMA, 季节和非季节性单变量模型的极大似然估计 + ]& x' l3 K! ^& {8 ]' `' n
Arithmetic grid paper, 算术格纸$ y2 _7 I. q) N8 Y( }+ m! F
Arithmetic mean, 算术平均数4 ^; d9 i6 X! K8 o1 h- U7 C
Arrhenius relation, 艾恩尼斯关系
- ]/ N5 P, L5 k, i$ c" @Assessing fit, 拟合的评估
; T/ h+ y8 D8 v, w2 o6 ZAssociative laws, 结合律
$ V& U/ R" D) P. H1 Q" w$ oAsymmetric distribution, 非对称分布/ T8 e5 `9 Y0 t6 @ n1 q) ]- a, K
Asymptotic bias, 渐近偏倚 s7 q1 u4 D( i! D4 z8 k, }5 J2 w
Asymptotic efficiency, 渐近效率) S) H9 ]$ L0 x$ w4 ^
Asymptotic variance, 渐近方差8 ], Y, w* d O! f
Attributable risk, 归因危险度
; v& g$ i; t0 eAttribute data, 属性资料
0 D/ |" L b+ ^5 vAttribution, 属性
# ~# i" I4 s- sAutocorrelation, 自相关# i2 `& }4 I5 C: t
Autocorrelation of residuals, 残差的自相关6 v/ m, a3 l1 Z) j6 M3 W4 y
Average, 平均数7 i5 l; n# l7 j9 G% \
Average confidence interval length, 平均置信区间长度
$ ~( n9 D6 e, mAverage growth rate, 平均增长率
0 ]& y) a9 V# |7 t$ U, lBar chart, 条形图
; [% m3 B0 E5 r* i! N3 \5 N, RBar graph, 条形图
8 |( G+ ~4 }% e% ZBase period, 基期
j! z9 }0 \. j0 f4 wBayes' theorem , Bayes定理3 a4 H0 a4 S9 t8 G+ [3 Z
Bell-shaped curve, 钟形曲线5 L& x* Q' J- t. V$ n0 t4 @/ d
Bernoulli distribution, 伯努力分布
4 \9 H8 V# p7 w; MBest-trim estimator, 最好切尾估计量' U1 X+ o O! ~9 R4 a
Bias, 偏性/ O" E6 j; m( k# _$ l* l4 o
Binary logistic regression, 二元逻辑斯蒂回归
" y# d/ e h9 h& jBinomial distribution, 二项分布; M/ z. H( `8 S/ L
Bisquare, 双平方
( ~, E) ~2 f9 ~. I% ]9 LBivariate Correlate, 二变量相关: x: p( ?2 t; w; G4 ^
Bivariate normal distribution, 双变量正态分布& i2 g6 x; Q% y& n: {
Bivariate normal population, 双变量正态总体3 v9 e% D7 _. P" S+ M
Biweight interval, 双权区间: {/ w `, k6 L8 m3 p
Biweight M-estimator, 双权M估计量# o* Q7 ~: ^$ Y; e; ~# F1 A
Block, 区组/配伍组" N0 j) Y0 z, u
BMDP(Biomedical computer programs), BMDP统计软件包( _. f5 r7 d$ \0 x' @
Boxplots, 箱线图/箱尾图 b" j9 l$ s0 X! }! u, S
Breakdown bound, 崩溃界/崩溃点' F( a+ u; J l
Canonical correlation, 典型相关; s: V# G( I6 ~+ E
Caption, 纵标目
. r5 [7 S( b8 f0 o* FCase-control study, 病例对照研究
4 H9 q& B5 m6 p+ e; KCategorical variable, 分类变量! {; c# c. v+ y: c/ M' [/ F/ T. v
Catenary, 悬链线" r* T1 {! [5 q
Cauchy distribution, 柯西分布
0 F: V, k) U1 ^- D1 ~5 } FCause-and-effect relationship, 因果关系
* Z% T( Z! b: k' B$ D9 F/ GCell, 单元/ z4 ]# a, }$ R( @ N' {* \
Censoring, 终检
! i7 ?5 U9 ]! t; jCenter of symmetry, 对称中心5 x v0 ]* f1 K3 \% s% ^+ h
Centering and scaling, 中心化和定标
6 o: ?& z0 r% Z: C- KCentral tendency, 集中趋势( A: u; F- Y F# i6 [
Central value, 中心值
2 M8 i1 h" L; SCHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测" U9 p5 W ]. @7 Q8 l& Q" K2 Z
Chance, 机遇
8 H* t0 c I# r9 gChance error, 随机误差
( V, p2 s: c- I: }& ?: IChance variable, 随机变量
9 l! S( X3 m3 ?) n5 b! v" S' XCharacteristic equation, 特征方程
% P" g2 Y) i# a# E/ @1 t6 ~Characteristic root, 特征根
# ]. T: Q& p: p9 I6 E1 [Characteristic vector, 特征向量- z9 s- a6 O7 n2 D5 y$ s
Chebshev criterion of fit, 拟合的切比雪夫准则3 e5 L2 v3 e' V
Chernoff faces, 切尔诺夫脸谱图
a% E* M' e* O9 E$ jChi-square test, 卡方检验/χ2检验% {; D1 k& x# F: q$ R3 i. u
Choleskey decomposition, 乔洛斯基分解
: X+ C8 J: n: \# z0 f1 c ~Circle chart, 圆图
- k, q% Q0 q3 Q0 zClass interval, 组距
& F! P2 [3 ^/ M8 U8 {8 VClass mid-value, 组中值
* A; n E5 }' RClass upper limit, 组上限3 i4 y( w* {6 l& q) F8 ^8 C4 ~( a
Classified variable, 分类变量) b1 C% Y/ T0 u0 k
Cluster analysis, 聚类分析
# h; O5 M4 \ C2 v, Y" o: uCluster sampling, 整群抽样- Q: `$ I+ D# j4 J
Code, 代码. |* K& {" r3 t" E
Coded data, 编码数据
6 P" c0 l/ S, A, SCoding, 编码
: u. S9 J% Z& m0 Y$ l) Z7 HCoefficient of contingency, 列联系数7 [+ l5 ^1 X6 u3 G, g( s4 Z z. u
Coefficient of determination, 决定系数
# ]5 g4 @* v6 C$ N: l$ ]Coefficient of multiple correlation, 多重相关系数
' o! ]% `! |+ p* i, K& Z5 k5 d' fCoefficient of partial correlation, 偏相关系数9 _: D) k6 C/ V( N1 t
Coefficient of production-moment correlation, 积差相关系数* R: ^, l4 h. q( ?
Coefficient of rank correlation, 等级相关系数
% V" }& ]( ? o: B) G/ V* i7 a6 l0 GCoefficient of regression, 回归系数) R* j% M" k% q( S: p
Coefficient of skewness, 偏度系数. K7 z0 c$ _% o( }7 v3 W& H
Coefficient of variation, 变异系数/ r$ ?3 E) I, G3 S+ J* J* J5 A
Cohort study, 队列研究
) w9 Z* _/ ]+ S3 T& FColumn, 列, Y1 F7 L. E9 ]: A( F1 j8 L
Column effect, 列效应/ d/ a* C3 C) x' d
Column factor, 列因素
, ^% f) s. I$ v) KCombination pool, 合并2 ~( d5 E0 O0 Q% H% A
Combinative table, 组合表
/ G9 J/ a3 Y3 F4 A' F' ^Common factor, 共性因子+ J7 v, y7 ^6 P: L* x) H
Common regression coefficient, 公共回归系数
8 i! v7 U- `7 {, a0 r# HCommon value, 共同值7 X/ W$ l# R: j* o# B9 ?$ ~7 h
Common variance, 公共方差% z5 B! I" n, ^! R
Common variation, 公共变异1 ], b& |# @) a- L0 [# m0 i) q! j
Communality variance, 共性方差
3 R# j/ R& b+ B- r, b7 ^. |7 G+ yComparability, 可比性
7 [5 O, T* F5 ZComparison of bathes, 批比较
) K9 l, q* z, b) [3 z( g7 VComparison value, 比较值( A% Q2 b0 ?, o0 y
Compartment model, 分部模型
' u' }9 k8 {. D6 VCompassion, 伸缩
" H2 W# M# q3 q2 y0 ~/ mComplement of an event, 补事件! M) `2 a, T/ i+ M
Complete association, 完全正相关
& @8 D7 n7 T, m9 i8 G1 MComplete dissociation, 完全不相关
3 T2 q$ I1 O6 H; pComplete statistics, 完备统计量
# o4 A- J' y7 f CCompletely randomized design, 完全随机化设计$ ?& O m4 N5 F
Composite event, 联合事件0 l( u; e- }+ `+ s
Composite events, 复合事件$ L& n. E' z/ T0 }8 U: w9 K8 |! R
Concavity, 凹性
8 ^ D0 R; ~4 T4 T- |Conditional expectation, 条件期望7 i; _) M3 f3 B5 \6 a \0 o0 T
Conditional likelihood, 条件似然
; O& P7 r4 X. Z9 bConditional probability, 条件概率
# ^+ u: s* z! V7 e3 pConditionally linear, 依条件线性- M0 d; h2 r* z& \- R! _# h6 s
Confidence interval, 置信区间
; ]- M2 B8 S- TConfidence limit, 置信限# p% A' j& Y; @7 R8 G& G; H
Confidence lower limit, 置信下限
! s8 D! ^& Q' S2 \% rConfidence upper limit, 置信上限
0 a: y2 `3 p: B, \. S+ q( [Confirmatory Factor Analysis , 验证性因子分析
2 m. R G7 B1 N- s9 FConfirmatory research, 证实性实验研究
$ J6 g7 l @0 w) Q! k) QConfounding factor, 混杂因素. H* m- K+ _& ]. J
Conjoint, 联合分析
% c {: z( x$ Y0 z+ Y3 cConsistency, 相合性, e6 ^- U5 Y2 l1 }2 A- d
Consistency check, 一致性检验) g$ [) a! {% s* |1 r ^
Consistent asymptotically normal estimate, 相合渐近正态估计
- S; ^* ~/ s' H( N/ hConsistent estimate, 相合估计
* l$ P$ j# |& AConstrained nonlinear regression, 受约束非线性回归
" O0 h8 t9 a* f: zConstraint, 约束
; q' K. W& G) v& a# ?Contaminated distribution, 污染分布 Z- O6 t& ~0 |4 S; n
Contaminated Gausssian, 污染高斯分布
a7 C! s/ v( B9 I7 N* SContaminated normal distribution, 污染正态分布8 J, J/ M' x, G( H$ R
Contamination, 污染
- D4 W& e* H. p7 |( r( ?) i& H9 GContamination model, 污染模型
3 P# V: E# `: U$ N* B+ ^Contingency table, 列联表
% S( |% }9 n. j7 v1 Z# @4 KContour, 边界线7 d- @. h- _& G( n
Contribution rate, 贡献率" Y2 P' M$ d2 A8 d; p, C+ T6 `
Control, 对照) M, p6 B2 X' r! k( n
Controlled experiments, 对照实验! W, V# V% g$ w- G6 y# [
Conventional depth, 常规深度5 W$ J/ {/ n; n+ L5 ~1 w
Convolution, 卷积 D/ Q1 g( t7 V( [0 v% P
Corrected factor, 校正因子# ~$ h* w- p" l. k; P
Corrected mean, 校正均值- V0 j/ |! C- @" S
Correction coefficient, 校正系数
$ ~' C6 Z/ H% M, h. ~, nCorrectness, 正确性% a. d* V( m! ?" ^' `5 V4 b3 b
Correlation coefficient, 相关系数3 Y. q: Y, a, a f
Correlation index, 相关指数
8 ^8 L% G' o/ @" d- k$ _* M. _Correspondence, 对应
8 w$ C5 \/ r# e. ]4 bCounting, 计数
* b% k4 J+ Q1 \: w% B0 YCounts, 计数/频数
7 P! C* u" V2 l. Q( QCovariance, 协方差
4 q( a4 N7 s" GCovariant, 共变 + c1 U% \% T3 w
Cox Regression, Cox回归
5 `* j1 A; `- YCriteria for fitting, 拟合准则
4 Q/ d! c5 }4 c1 {Criteria of least squares, 最小二乘准则& o9 r: c( p9 x( V" _: l
Critical ratio, 临界比" T. |" J. a3 Z" B" O! j
Critical region, 拒绝域
! X/ C4 l! w3 f7 S3 d8 j3 oCritical value, 临界值$ E9 ~, a6 d" \2 V
Cross-over design, 交叉设计
! O' n# V3 J' W- {9 ?: V1 J% b; ]Cross-section analysis, 横断面分析
' I3 c+ a) }0 S3 J* `1 E6 SCross-section survey, 横断面调查/ M$ E8 E& n9 D5 `4 s3 z9 Y
Crosstabs , 交叉表 : H8 |$ a, n, H: d1 d; ^
Cross-tabulation table, 复合表
D) N2 z- {8 E. T; vCube root, 立方根2 K! @0 \1 Y2 t+ F. j$ L U5 M
Cumulative distribution function, 分布函数
. h! p% ]8 v3 \: F& gCumulative probability, 累计概率
2 n/ `/ T, O+ e+ s! u. gCurvature, 曲率/弯曲6 w: P. Q! r7 x+ R9 Q1 X9 ]" e
Curvature, 曲率
+ |+ R$ G6 ` t2 E3 ICurve fit , 曲线拟和
. W4 H% [2 |' @( V# L0 ICurve fitting, 曲线拟合
5 F5 S& a$ I1 A4 \1 q ~Curvilinear regression, 曲线回归
! _, W/ p+ u. \. ACurvilinear relation, 曲线关系- z$ Q& i' t; ^& _7 ?
Cut-and-try method, 尝试法
: U( e$ q/ f3 ^ e* d: F5 q8 BCycle, 周期# t Y. H$ n+ \0 f s7 f% u
Cyclist, 周期性5 X3 u* m' \* e4 ~/ W
D test, D检验* f7 A# S7 Q% I
Data acquisition, 资料收集 Z2 e- v: h3 V
Data bank, 数据库, F) a0 M; }) Y
Data capacity, 数据容量4 I1 J5 J$ j- l9 X8 x1 e3 Q
Data deficiencies, 数据缺乏: a- N) i: T# w/ j% P! a
Data handling, 数据处理. f; }0 v& ~* R+ s" k* ~. q. n# ]
Data manipulation, 数据处理
% N9 k; [% K& ^8 @" U9 QData processing, 数据处理
' X/ r5 z' @8 S0 QData reduction, 数据缩减( D! m0 \" s; s! L" u
Data set, 数据集* L# Z" c7 Q2 L+ k) L
Data sources, 数据来源
3 M' m; ^3 o7 F9 NData transformation, 数据变换
- u- S& C& v) ]$ a5 mData validity, 数据有效性" Q' A! e. s! i6 n
Data-in, 数据输入
: B2 r4 N, {- X: sData-out, 数据输出' v+ o) ~- O c
Dead time, 停滞期
1 S' v& f+ ]( g7 [: B% p$ aDegree of freedom, 自由度) K. H' ~( @2 k$ Y. Y
Degree of precision, 精密度& `/ `0 s) f% M* w& B1 j
Degree of reliability, 可靠性程度3 f- a) g: Q2 n
Degression, 递减
: _* o l- ^/ V4 h* qDensity function, 密度函数6 B @* ~- ~. A) G9 m5 |
Density of data points, 数据点的密度
7 H/ V8 o$ Q9 k5 [$ H6 o' `Dependent variable, 应变量/依变量/因变量
/ ]3 d% s" I6 I0 W! O# YDependent variable, 因变量9 I2 ~; O0 R7 ]2 h9 Q3 x$ [
Depth, 深度5 B( b" M5 y: R% t4 Z5 }
Derivative matrix, 导数矩阵6 r- n' f# ]0 b1 a# a- A
Derivative-free methods, 无导数方法0 ]' C7 p J4 M0 O$ m3 q
Design, 设计
, W1 v7 F6 s! _Determinacy, 确定性
/ h9 }+ E" e x7 e" m7 D5 O6 T5 z* uDeterminant, 行列式
3 w3 D: j/ c6 q0 ]- _2 C" ^) }9 xDeterminant, 决定因素4 d4 u9 e* P' J4 E$ J
Deviation, 离差" Z `) _& C! u1 a# z& o
Deviation from average, 离均差8 |4 S, H- c1 f; t0 O; s: n
Diagnostic plot, 诊断图# j, _, C! S$ l4 g( {6 q
Dichotomous variable, 二分变量
) s! i, z( q' @Differential equation, 微分方程
5 Q& T% ^0 X! q0 y mDirect standardization, 直接标准化法
2 H' I: L N1 Z l V' \; oDiscrete variable, 离散型变量* f9 Y) S+ [( u' ^% w( U
DISCRIMINANT, 判断 5 N7 v0 k# T3 @3 }; M
Discriminant analysis, 判别分析 q& p U0 D8 ]* L& [
Discriminant coefficient, 判别系数
0 b# Q% V, n, M; r2 Q( YDiscriminant function, 判别值
0 t" N l( D9 G, `. N6 i+ LDispersion, 散布/分散度
! F4 z3 Y8 b9 i2 ]Disproportional, 不成比例的3 M! n) R7 n7 z$ O. |1 L
Disproportionate sub-class numbers, 不成比例次级组含量! x9 Q. b" d6 f% h# Z; F7 L
Distribution free, 分布无关性/免分布
2 ^- h0 s% A; s! HDistribution shape, 分布形状/ H! A9 R6 c" Y+ C
Distribution-free method, 任意分布法1 F# J! u* M1 C! c! }
Distributive laws, 分配律* P8 K+ g+ k! `/ K# J
Disturbance, 随机扰动项
+ O0 _' C7 r+ Q, [& B" K/ CDose response curve, 剂量反应曲线
% s& L! J6 P5 P8 f& J, IDouble blind method, 双盲法
) r1 P! L6 ^% e( C" M+ c8 n& pDouble blind trial, 双盲试验6 \1 B+ ?5 H5 V% a
Double exponential distribution, 双指数分布
5 R# H4 d9 N' _1 q$ H8 uDouble logarithmic, 双对数$ @" @5 f* A* {3 V, ^* \7 z+ N# X; Q
Downward rank, 降秩
$ g* g1 z. w( u; {9 q( A( B# uDual-space plot, 对偶空间图
2 L6 \4 s- M6 ~. ?# T2 WDUD, 无导数方法! F$ y3 Z4 K- ]0 R+ d: N
Duncan's new multiple range method, 新复极差法/Duncan新法
# K. A* q7 X4 J9 YEffect, 实验效应! _, k( I. W) b) n+ x D
Eigenvalue, 特征值) ^' J1 \ B5 y( l4 u+ N. _
Eigenvector, 特征向量
" D8 B: [, o# a0 H% `; h+ B: nEllipse, 椭圆0 R% f; x8 s3 i. J: O9 A2 ? q
Empirical distribution, 经验分布2 s. w& z" c8 e& o) h- Y, N( _3 e
Empirical probability, 经验概率单位4 a6 W* Z4 _/ P" w0 I# J% k
Enumeration data, 计数资料
8 T' o. I& N- y4 u7 @5 C+ v0 R. bEqual sun-class number, 相等次级组含量- l5 n! K) }" v: H6 [8 H8 {
Equally likely, 等可能
7 i2 l8 V. P n1 [2 b9 p( bEquivariance, 同变性# w- M" l! S0 r1 h) W
Error, 误差/错误/ i L3 A7 b( p# s, T& x! V$ q
Error of estimate, 估计误差7 \( X/ D1 E3 ?) \3 v) p
Error type I, 第一类错误. B/ t, P7 Q# {& n/ q, U$ A: t; t! n
Error type II, 第二类错误2 @' c& \; u+ r. ]4 C2 Q, R9 h
Estimand, 被估量% P3 o1 J9 b. w
Estimated error mean squares, 估计误差均方
) ]8 j2 K$ L) C8 {8 dEstimated error sum of squares, 估计误差平方和% e- D# R! L2 T1 L7 C
Euclidean distance, 欧式距离
7 f! T1 k2 Z) P+ ~Event, 事件
, x/ W! T6 t1 W! P4 h8 c. iEvent, 事件
8 y1 L- r" e6 [9 ]3 L+ n' lExceptional data point, 异常数据点& s E( G: G9 k3 E
Expectation plane, 期望平面
" a6 J/ K+ N5 u7 b# Y) QExpectation surface, 期望曲面0 C' [3 a$ b9 | a3 F% S* y" S4 P
Expected values, 期望值
, m% \1 B: f5 l4 _1 t$ C8 y) l2 W2 w0 EExperiment, 实验5 t# a f% A! V! T/ ]# ^
Experimental sampling, 试验抽样
, C" f& ^" G* S5 R( I" kExperimental unit, 试验单位
% V9 Y, m' D+ Y% Q* D2 oExplanatory variable, 说明变量" _5 j" g* i s# U) H4 k4 K u* N
Exploratory data analysis, 探索性数据分析8 x3 |0 x2 Z6 M2 y2 v" s
Explore Summarize, 探索-摘要$ L, \- t3 n ]+ t% M+ L; f
Exponential curve, 指数曲线5 c. J+ `2 d4 ]7 H
Exponential growth, 指数式增长
5 O1 F% o3 G8 B' k6 B8 Z! `9 tEXSMOOTH, 指数平滑方法 9 U6 m" ^" Y" t6 o7 X6 o
Extended fit, 扩充拟合
; C" r! ?4 ^9 E, ? J" ]. NExtra parameter, 附加参数
+ U. W* U$ _9 r9 z8 f2 q# vExtrapolation, 外推法
7 y7 \ V: ~- K) J, o& hExtreme observation, 末端观测值& }3 ^5 g; m+ `4 G7 F
Extremes, 极端值/极值
- |) D ~1 g1 e/ {. e9 }F distribution, F分布
/ F) ^% v6 m GF test, F检验
5 e+ r3 X( _- w+ T+ j# i1 kFactor, 因素/因子
; V9 [1 u( x$ ^2 i9 X- T: gFactor analysis, 因子分析5 ~3 a; t! G+ w5 C3 y) {
Factor Analysis, 因子分析. U% }0 ~. I* a" `4 J
Factor score, 因子得分
( ^$ b; ^/ d5 k/ H0 h% YFactorial, 阶乘+ A0 V2 g2 [1 q% _2 k5 {# B- @$ Y2 y
Factorial design, 析因试验设计" ~! f/ P& W4 N4 O
False negative, 假阴性
' s6 n' s6 q; uFalse negative error, 假阴性错误* E. X' S' ]+ ?" b Q
Family of distributions, 分布族
7 d# B4 E0 W( N% \ U0 TFamily of estimators, 估计量族8 A: w2 @/ ]% v( F
Fanning, 扇面
# V p. C, Q# ^8 y" \9 qFatality rate, 病死率7 D" S( Q9 a% x
Field investigation, 现场调查$ X: @5 K. B9 U
Field survey, 现场调查
4 X6 `- X; s% Z4 i3 J# pFinite population, 有限总体
- U: M" [+ u6 D. {) Z& N* V7 GFinite-sample, 有限样本) ^! U& k; c0 }: q$ k' v- r2 c
First derivative, 一阶导数3 X6 v h+ _) B+ n
First principal component, 第一主成分
4 i# |$ b. @! o1 q. |' Z( H( KFirst quartile, 第一四分位数
4 t8 c+ z7 m( a# Z4 aFisher information, 费雪信息量; K8 X& A+ I) j! T
Fitted value, 拟合值( }% J; _9 f# [$ U, k% e) B
Fitting a curve, 曲线拟合 _5 J- y2 X4 K7 a' @
Fixed base, 定基4 V. k$ K: A1 F- S t- E
Fluctuation, 随机起伏/ J0 U( _3 h) S9 g! G$ `
Forecast, 预测- F; x9 B7 c" Z9 L; x* e7 j$ p( U
Four fold table, 四格表
. c4 S3 |- ^9 [6 ]( x2 x. F6 x0 OFourth, 四分点
( X5 C; C% e; W) VFraction blow, 左侧比率9 }" b w' L3 J; w8 j
Fractional error, 相对误差: ~- s- T& ^7 r, e: }# U
Frequency, 频率. Q% N W. s8 U8 \# S
Frequency polygon, 频数多边图
" m8 H% h" K. j4 {; I+ wFrontier point, 界限点; a5 p. M5 E# r3 e5 {
Function relationship, 泛函关系
5 a" i* C/ N. p- q6 @0 cGamma distribution, 伽玛分布
8 f& X6 s. Z" f- VGauss increment, 高斯增量
; C- P7 l5 ~. ^5 G, S+ TGaussian distribution, 高斯分布/正态分布& E) Q9 ]/ |9 m: } q/ a' K
Gauss-Newton increment, 高斯-牛顿增量
6 P: d8 `. {9 g0 W" W4 J" kGeneral census, 全面普查
/ E1 S/ e1 E% L8 x: TGENLOG (Generalized liner models), 广义线性模型
3 D. s' F0 [ O; D( Q% K" Q: qGeometric mean, 几何平均数- a* ^1 z" X3 {
Gini's mean difference, 基尼均差
1 F2 O, Q* [8 F9 GGLM (General liner models), 一般线性模型
8 \: w7 X- S/ V$ aGoodness of fit, 拟和优度/配合度 N9 {/ N4 |, A1 ]3 {5 E' ]4 `
Gradient of determinant, 行列式的梯度" C, Z8 Y9 I# U* X- A) P, T& ?1 j2 o
Graeco-Latin square, 希腊拉丁方
+ m6 N: t' d7 i7 D# mGrand mean, 总均值
3 A6 C! p. T: _3 T4 k! x' uGross errors, 重大错误4 p9 z" V8 U: ^- s9 K
Gross-error sensitivity, 大错敏感度
# X& q2 V( p6 k# Q$ X4 X1 HGroup averages, 分组平均
, U2 K* |4 B4 @. q* TGrouped data, 分组资料
; ~# v) X" L+ nGuessed mean, 假定平均数
7 I/ k6 F* M+ Q' Z/ f! j; XHalf-life, 半衰期
1 }; s! j) d7 g5 @Hampel M-estimators, 汉佩尔M估计量( y/ u$ P0 `# k3 ?- H9 l& | ]) Y
Happenstance, 偶然事件
5 q* D, x! J. J2 y/ L5 i+ cHarmonic mean, 调和均数9 p9 J0 s6 X4 w8 m S& X
Hazard function, 风险均数
4 y( k9 Z; ^2 T1 V8 b- DHazard rate, 风险率
) A4 U3 E; ?) f0 Z' V2 QHeading, 标目
' e, s6 ^7 ~4 p+ b; T" Y5 OHeavy-tailed distribution, 重尾分布
0 Y* _! r$ V( k7 E) vHessian array, 海森立体阵- U- i0 q2 x) A& c# F P; o$ ]
Heterogeneity, 不同质
; e! J+ Q5 E. b& ]Heterogeneity of variance, 方差不齐 0 k2 x# A8 ~. Q0 u2 c
Hierarchical classification, 组内分组
# G1 {% E, g+ t2 U* V( N+ Z6 [Hierarchical clustering method, 系统聚类法: x: i0 ?# ?: L) r6 s. I
High-leverage point, 高杠杆率点
1 ?% w& h- D3 m, e, LHILOGLINEAR, 多维列联表的层次对数线性模型
- q4 Q: X/ i9 e6 LHinge, 折叶点
0 H* e/ h% E( B. d' `2 k# P4 g, LHistogram, 直方图
+ ?- e, j( F5 ]Historical cohort study, 历史性队列研究 5 B; ~* M+ }1 A7 b, C
Holes, 空洞( W! H2 @- C: k: j, v) y
HOMALS, 多重响应分析
+ e8 _% x8 ]" B \3 hHomogeneity of variance, 方差齐性5 l3 j8 v% ~' C
Homogeneity test, 齐性检验, y1 N- D2 b( B4 v- \" J7 T* p; p& h
Huber M-estimators, 休伯M估计量
* K( ~0 G" p( e! V4 a. j1 d" aHyperbola, 双曲线/ u t2 x4 C1 ]1 e7 }( d
Hypothesis testing, 假设检验2 a& {# j* V# Z% Z0 m
Hypothetical universe, 假设总体) K- P, k( ~ U2 t Y
Impossible event, 不可能事件
/ q9 C( i! ~' \) L0 aIndependence, 独立性
1 r5 K/ u: f+ }; X9 SIndependent variable, 自变量
, j( o% h! ]% L; y& r/ _4 YIndex, 指标/指数
: d2 S+ M) H* ?/ @6 k% _4 M1 Q$ bIndirect standardization, 间接标准化法
+ ~( N8 t3 S1 p7 c. N* RIndividual, 个体4 p8 T6 n, C, k& {
Inference band, 推断带5 C# @6 ^* S/ e% k. g
Infinite population, 无限总体, v2 h" p, Q( f
Infinitely great, 无穷大4 X, j( n0 R( l
Infinitely small, 无穷小: |! x* R7 R: P4 r1 e. G9 S
Influence curve, 影响曲线
^5 K/ F& A. j3 z/ o# xInformation capacity, 信息容量
7 [ k6 s: p N5 PInitial condition, 初始条件
6 g- _) s( i5 QInitial estimate, 初始估计值
1 T: t% z9 j6 \4 j3 MInitial level, 最初水平1 t5 o* J- k5 v3 @) ?, |
Interaction, 交互作用# c; q3 j6 S5 X) s; Y+ k. v% a( {% n
Interaction terms, 交互作用项
/ M. ]. Y& @/ a8 g0 P5 ZIntercept, 截距
# H2 M, j2 U" W6 `7 YInterpolation, 内插法
3 L9 N! X1 G sInterquartile range, 四分位距" u" S$ p$ W* v! l% F
Interval estimation, 区间估计
4 D9 v( D+ X+ o% rIntervals of equal probability, 等概率区间- ~3 W. _4 R3 `$ ^- t8 D& ^* c2 {
Intrinsic curvature, 固有曲率6 |- H, d; ]4 ?0 e0 A
Invariance, 不变性
+ _6 s4 h% r i8 X1 D$ U; DInverse matrix, 逆矩阵
1 I& X& a3 w8 J) IInverse probability, 逆概率" p: z! N. H6 A' N( ~' K1 a9 n- E
Inverse sine transformation, 反正弦变换7 ^4 e. u3 @0 C/ K
Iteration, 迭代
6 w5 \3 ~- D1 H; QJacobian determinant, 雅可比行列式7 L7 Y3 o+ P& Z. _: @: k2 c
Joint distribution function, 分布函数# Q; [( q* Y. i3 o- `
Joint probability, 联合概率6 u( F* S" y" g9 m- I
Joint probability distribution, 联合概率分布( P2 b+ o* p+ c4 ?2 S' P* o& v
K means method, 逐步聚类法
3 H: h8 e3 L$ c. a( lKaplan-Meier, 评估事件的时间长度
0 I8 I0 e1 C: l* m9 w- v; HKaplan-Merier chart, Kaplan-Merier图; z0 {& l2 X/ _: }% N
Kendall's rank correlation, Kendall等级相关4 N( F4 o# T- P) M
Kinetic, 动力学
4 S) O! F6 `6 S/ O* y1 ]9 iKolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验+ T9 F: F; V7 M2 F, \
Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验
$ E( c( R$ h. G: G9 P( k% k. K. QKurtosis, 峰度
3 d! B$ c) y, q8 }& H6 BLack of fit, 失拟
4 M+ E' s. b( J! S9 @Ladder of powers, 幂阶梯 L" d" D) ~% @% r3 w- O* h' }
Lag, 滞后" g+ f. C3 O: k3 q
Large sample, 大样本
( O; C. ?# y6 LLarge sample test, 大样本检验
) ?: ~& z6 t; ELatin square, 拉丁方# w3 f) q( I( y! k! |& C9 }
Latin square design, 拉丁方设计3 s" w$ r+ b* B' W; ?! Q) _+ M3 H
Leakage, 泄漏3 C3 ?2 w$ h: v/ p8 H
Least favorable configuration, 最不利构形* e* \9 @* a) ]# Y; _2 S4 C
Least favorable distribution, 最不利分布
5 c% G7 [0 x; W' a. z9 R& @Least significant difference, 最小显著差法
9 I# A7 }) t: M/ e& c& g! X) mLeast square method, 最小二乘法
! F5 ^ R: e- E. Z, [' xLeast-absolute-residuals estimates, 最小绝对残差估计
) p5 l' t# z2 b U* j, |% PLeast-absolute-residuals fit, 最小绝对残差拟合0 {* Z0 v9 U* y6 k- \' O( Q* f$ G& I! u
Least-absolute-residuals line, 最小绝对残差线3 o }% x. r; |+ o+ X6 I |
Legend, 图例8 C, Z% K) M+ h7 W9 C, J! T
L-estimator, L估计量
; g8 G# a/ i: n3 Q" F6 `L-estimator of location, 位置L估计量9 k- @' h$ R- |/ d1 X! I. o
L-estimator of scale, 尺度L估计量% l1 D0 Q2 E) A/ J+ Z
Level, 水平
1 L, N9 i( O; s- V: qLife expectance, 预期期望寿命
R. o1 W! S) L" \" L) h' p: _Life table, 寿命表' R7 J/ @- |% } p
Life table method, 生命表法
2 Z6 t5 m+ D) Y, ?' cLight-tailed distribution, 轻尾分布
0 L8 \* C% C. P6 [: O2 @Likelihood function, 似然函数0 l9 h8 K5 ?; i8 l+ J+ k+ R. e, `6 e
Likelihood ratio, 似然比/ |; ]5 t- M# F/ ^; ~1 t
line graph, 线图+ f: l g+ [' E, i5 D+ H$ Z6 O
Linear correlation, 直线相关" _6 E6 V7 [: @8 _2 S" q8 ]/ s
Linear equation, 线性方程
4 b+ m/ m: Q3 m+ j" v- e/ @. O$ ULinear programming, 线性规划
6 I2 Y* P. ?: y: R& J& N/ ]Linear regression, 直线回归
" g1 ]3 \. g# W( N: q/ L! FLinear Regression, 线性回归+ e5 F: ~8 q% e" ]- A" ?
Linear trend, 线性趋势
2 g' B5 Q, p8 |6 O9 Q/ O( W3 bLoading, 载荷 ; n# z: c: x) u7 Y
Location and scale equivariance, 位置尺度同变性( q# x0 X% D# y, |* t
Location equivariance, 位置同变性
) d9 F# e" a: U i4 ?Location invariance, 位置不变性6 F; D* T0 \/ Z) d. X, L! C2 x
Location scale family, 位置尺度族' _0 L% O) i, m2 Z0 M
Log rank test, 时序检验
; [% H, G# J6 I/ ]Logarithmic curve, 对数曲线
( v7 a3 p# P# j, @- b/ ?* ILogarithmic normal distribution, 对数正态分布" P8 r/ p# b9 H
Logarithmic scale, 对数尺度 d3 v, e0 J E0 V! V7 o
Logarithmic transformation, 对数变换- y" Q1 P q' {+ `
Logic check, 逻辑检查$ u& F5 ]' {5 y* x
Logistic distribution, 逻辑斯特分布8 b, t! A; ~5 N z- V5 T1 Z/ ?# e
Logit transformation, Logit转换
- X9 l8 ]5 m! R' c' c4 m2 |LOGLINEAR, 多维列联表通用模型
$ \- \/ p8 b% P& k3 S, X3 t5 `Lognormal distribution, 对数正态分布' }" y2 [3 C! r! F4 r3 A1 Q
Lost function, 损失函数6 j* V- C( {" ~
Low correlation, 低度相关
& @2 m% R# o7 \4 Z* |0 Z0 }Lower limit, 下限$ e! k; ?6 X: Y' {5 `) {/ [
Lowest-attained variance, 最小可达方差
- [" S: W- U0 h* @LSD, 最小显著差法的简称6 F- k/ H8 q3 p
Lurking variable, 潜在变量
9 D$ N, Z1 l3 j6 K* a& h/ `Main effect, 主效应+ s/ o1 w; S; J9 {
Major heading, 主辞标目
6 S* r- j: }4 J+ oMarginal density function, 边缘密度函数$ j8 u7 f4 ~& |
Marginal probability, 边缘概率
# I; j/ K# P D5 l; CMarginal probability distribution, 边缘概率分布' D' }6 \( f2 o2 P: p- n
Matched data, 配对资料0 Z2 `$ P9 v& R; J* H3 W5 J& n
Matched distribution, 匹配过分布
* {, V6 q9 c' I/ k5 | F' y8 EMatching of distribution, 分布的匹配! {% m* ~1 D {( b7 C, L
Matching of transformation, 变换的匹配
# b; b: ?4 \$ }; k0 X3 yMathematical expectation, 数学期望
& e% V4 E3 h2 h a. F7 JMathematical model, 数学模型& T. N. d8 `( A
Maximum L-estimator, 极大极小L 估计量8 a5 e! f0 n% d
Maximum likelihood method, 最大似然法
0 `$ T+ A$ f) t" a$ N w" [+ S7 @+ QMean, 均数
( J( E, s3 K/ s9 G: RMean squares between groups, 组间均方. S6 @3 r4 h% l% `
Mean squares within group, 组内均方, o/ m1 {: Z, _
Means (Compare means), 均值-均值比较
8 r) v9 O2 s R8 g3 L$ [% bMedian, 中位数
0 A6 Z8 I4 M- Q: w, Y# P3 pMedian effective dose, 半数效量
/ \: Y3 h$ z4 u5 d8 ?& T5 w# KMedian lethal dose, 半数致死量
9 O$ s1 s, G& x, gMedian polish, 中位数平滑
! t& G" x' ?6 q9 ?Median test, 中位数检验/ z% S* s# i% a5 }2 p; z
Minimal sufficient statistic, 最小充分统计量$ B. Z# d3 {9 _3 A
Minimum distance estimation, 最小距离估计) M! d' F g0 d% }
Minimum effective dose, 最小有效量6 l& m. @7 S2 x! A* }4 B( O" K
Minimum lethal dose, 最小致死量& C# x ^( h" k. b* a4 {; S3 C' l1 l0 s
Minimum variance estimator, 最小方差估计量
1 j- Y7 O; h" `MINITAB, 统计软件包
* N0 @0 o6 c0 J! O: L5 X" jMinor heading, 宾词标目
2 B. P* p& ~4 A- L0 `Missing data, 缺失值
- R$ V' Q, ^6 A- _) Y( F+ q1 sModel specification, 模型的确定# D4 {6 b3 ]+ L- `! `- r
Modeling Statistics , 模型统计
4 W% R3 j8 `" p2 OModels for outliers, 离群值模型2 H9 t+ x: a( }: Z; V) B7 ]
Modifying the model, 模型的修正
3 c* {; B! Z- C h- F0 X M8 \Modulus of continuity, 连续性模$ x: E5 j- z0 f7 S
Morbidity, 发病率 0 ]$ _7 ^) g" J3 `/ D F
Most favorable configuration, 最有利构形3 ^8 q8 t" n% j( J' E9 a+ [' e
Multidimensional Scaling (ASCAL), 多维尺度/多维标度
9 i: V: X, t$ C5 _Multinomial Logistic Regression , 多项逻辑斯蒂回归* P; U9 D# D" k- |( W8 q0 w
Multiple comparison, 多重比较
- ]' F7 v4 F: t8 Q' b9 V; \8 lMultiple correlation , 复相关
+ M! n, n" L7 pMultiple covariance, 多元协方差
) i) a3 W+ P" E, `9 A. U9 t: }Multiple linear regression, 多元线性回归
. P. N) L) {1 j6 [5 |Multiple response , 多重选项 M" C7 T. u4 T2 K: [9 H! I" v
Multiple solutions, 多解
) g X' D1 X3 L* jMultiplication theorem, 乘法定理
9 A7 z/ F0 k% }% I/ SMultiresponse, 多元响应% d' w$ f1 L- p) n
Multi-stage sampling, 多阶段抽样
i9 f5 ]9 W9 k. V; v+ n0 SMultivariate T distribution, 多元T分布
* b$ a0 H# J6 ^! s1 p6 Y* Y8 @Mutual exclusive, 互不相容9 w2 V5 o5 f2 J4 ?; y6 Y
Mutual independence, 互相独立
% c: g V+ l# k( h# bNatural boundary, 自然边界
7 |: c8 d1 Z0 k7 K/ B) s3 PNatural dead, 自然死亡
f* r4 R+ I) {4 C3 F3 j/ N# [Natural zero, 自然零
. A) a2 l% I# `! Y* w9 k$ fNegative correlation, 负相关 l# \ s# h! H( X9 B
Negative linear correlation, 负线性相关
: [$ a+ K" W% o2 d8 Y$ Z! TNegatively skewed, 负偏; ~" o, M9 J; _2 {: s
Newman-Keuls method, q检验4 J3 {9 @$ U$ N9 N
NK method, q检验
% t, a9 T q3 I/ ^No statistical significance, 无统计意义3 r. R6 ~; _4 L
Nominal variable, 名义变量9 U" d8 j2 y+ O% f* o! L, t: m
Nonconstancy of variability, 变异的非定常性
8 J& c S1 K+ U: y6 C& vNonlinear regression, 非线性相关
/ _3 p& Y9 p7 _5 `' G" LNonparametric statistics, 非参数统计
0 x: e4 R: u/ q/ W9 wNonparametric test, 非参数检验
( ^0 P! F2 \5 u, q! t4 wNonparametric tests, 非参数检验, c# ?6 N" Y/ O6 O
Normal deviate, 正态离差5 z2 j5 m6 z, [& E8 ~) w9 K6 ?% n% E
Normal distribution, 正态分布
" i r2 b, y {7 W. uNormal equation, 正规方程组; x2 \* w' D- U# Y. t. R8 ?
Normal ranges, 正常范围) k2 W. `+ R. n5 N1 Z0 l2 p
Normal value, 正常值. b# W% Y4 b; a3 y( [; O% l
Nuisance parameter, 多余参数/讨厌参数
3 J* ]! m0 x! S5 sNull hypothesis, 无效假设 ; V3 r2 h5 O. L3 h O6 G; A8 A
Numerical variable, 数值变量2 n$ h/ L9 b3 b3 e
Objective function, 目标函数. C; X% i6 f& I; N& ~
Observation unit, 观察单位6 X7 Z; D# v: M" o, {5 W2 a
Observed value, 观察值
' p% g& f6 ]. }2 [7 FOne sided test, 单侧检验& E; b5 H- a* t" P; q# n
One-way analysis of variance, 单因素方差分析
; Y* J$ c* N |% G0 L5 X) u! kOneway ANOVA , 单因素方差分析) k' t# z J6 [
Open sequential trial, 开放型序贯设计
3 J5 n5 P: t. l- Z3 pOptrim, 优切尾, U3 V5 M7 e' y$ |
Optrim efficiency, 优切尾效率2 E E; Y5 d3 R5 i( B
Order statistics, 顺序统计量' Y8 f5 [0 M8 h
Ordered categories, 有序分类. [/ j: h5 J* `7 U- }& X
Ordinal logistic regression , 序数逻辑斯蒂回归+ d, ~) @7 c7 x2 [" E$ {
Ordinal variable, 有序变量
! A; {6 L& v; L3 yOrthogonal basis, 正交基
/ p& l9 e# T: t4 @Orthogonal design, 正交试验设计# s) ]2 G- }: {! v. B
Orthogonality conditions, 正交条件- o1 C0 J+ y- {; j
ORTHOPLAN, 正交设计
; m8 N x& U3 I b/ DOutlier cutoffs, 离群值截断点
q, n w7 t! b! l1 y2 ?% \Outliers, 极端值
5 M. I" }& s) e7 F9 r: x& ROVERALS , 多组变量的非线性正规相关
# [3 B g. p6 d8 L- P) HOvershoot, 迭代过度
% }4 c8 T% u' o. m3 b3 ~Paired design, 配对设计7 r$ k- r6 ~% Q) q8 k) T1 q
Paired sample, 配对样本' M2 q" b4 A! o( X* F+ O
Pairwise slopes, 成对斜率6 x" C( s# ^: r* i
Parabola, 抛物线5 v; ]3 i6 T) [8 @2 Z$ O& z
Parallel tests, 平行试验
5 P0 T6 }4 D7 i1 `& sParameter, 参数& a h0 U. y: d3 X
Parametric statistics, 参数统计: T8 ^' @( `3 Q* n
Parametric test, 参数检验
3 `- o) k- N' ?; ~6 N- M0 FPartial correlation, 偏相关
3 X' z2 {& c* _' J$ E4 c! nPartial regression, 偏回归
# V6 L0 c: o z& n) F( RPartial sorting, 偏排序
; k: a7 q0 }% YPartials residuals, 偏残差
* G2 ~ V4 N2 b' G( {Pattern, 模式% a/ Q0 g$ C6 p( I$ o
Pearson curves, 皮尔逊曲线
3 S8 E3 r& |* r3 E8 N% dPeeling, 退层1 h+ v2 ]" e4 O8 o$ |5 ?' e6 T6 t
Percent bar graph, 百分条形图
: A0 P( S# O1 V* wPercentage, 百分比
- |/ ]- D6 l" z3 v n* `1 Y3 ?Percentile, 百分位数4 W: d: D! b: J R1 R; {
Percentile curves, 百分位曲线
' n+ _* s: Y% U& y$ @$ i: dPeriodicity, 周期性% S/ d, c& y N$ @( y& ?8 J t+ h
Permutation, 排列) e9 y$ y" P& p; | @) ~+ K9 U
P-estimator, P估计量
9 A/ B8 L7 M. V; HPie graph, 饼图) a& N. @: v. }
Pitman estimator, 皮特曼估计量
0 }% K9 g' U: GPivot, 枢轴量
; Z. k4 D; Q0 d* s" ?5 GPlanar, 平坦" H- K& a9 N+ N7 \- c
Planar assumption, 平面的假设0 S0 ]/ p( P9 `3 ]! v
PLANCARDS, 生成试验的计划卡
8 J N7 x4 ^3 Y: @) G# k `7 lPoint estimation, 点估计
! f* [9 |. ^1 ?# e' n/ gPoisson distribution, 泊松分布
2 L, v, P8 ? V/ ~7 F3 W4 C# dPolishing, 平滑
. d# z2 c+ M, P P7 H0 B/ b, `Polled standard deviation, 合并标准差4 b T& b2 S4 u0 m* D: ~
Polled variance, 合并方差1 {5 F) V: ^0 ?, m! k" }
Polygon, 多边图5 m6 l' K+ P& M( I, u8 H( S
Polynomial, 多项式9 r& `3 d8 l# t+ Y, [; K. C
Polynomial curve, 多项式曲线
6 a- H2 q- U1 {* APopulation, 总体$ A C: H6 h* W, [2 S8 S
Population attributable risk, 人群归因危险度* J& f# f9 C! j$ r# K
Positive correlation, 正相关! _- U: I1 A; s$ z$ ?6 k% i
Positively skewed, 正偏
$ m1 _0 v$ k" V, TPosterior distribution, 后验分布3 a) J' Q! \8 i' v$ O+ M; }- s7 }2 \
Power of a test, 检验效能
( }: m% n$ a9 H1 _0 @Precision, 精密度
# X8 w' a4 |7 p' _, F2 k- T& K$ qPredicted value, 预测值0 n7 t* m9 B/ T+ n) r+ w6 F/ d2 j
Preliminary analysis, 预备性分析
/ m2 i, Y% o6 e \Principal component analysis, 主成分分析
- |1 b* V" J x: u3 ePrior distribution, 先验分布. b( }" l6 t% o6 w- F
Prior probability, 先验概率! k l2 k7 K# ~' P# D3 R
Probabilistic model, 概率模型
4 g! ?+ m5 G; d6 X9 D7 \probability, 概率2 U1 b8 n% l, |/ ?# A
Probability density, 概率密度& p: c& `% I- g8 ^
Product moment, 乘积矩/协方差+ d J) A' Q' _7 r' F& p5 f
Profile trace, 截面迹图
& j7 f- M& t: Y eProportion, 比/构成比
( W1 _6 b9 [8 A( ]/ zProportion allocation in stratified random sampling, 按比例分层随机抽样4 x) u5 ~' Z* P2 u$ K, I4 F# J
Proportionate, 成比例
% s* u& j9 S+ \/ x. g$ KProportionate sub-class numbers, 成比例次级组含量, F4 P1 n8 o* |* A: R ?+ M
Prospective study, 前瞻性调查1 g8 h! B, ^. c0 Q' `
Proximities, 亲近性
% T0 `) A) }: S l/ Z' j) _Pseudo F test, 近似F检验% F5 k& l* Q$ c5 E2 w- ]
Pseudo model, 近似模型
+ Z) n: A1 `9 [, }6 H7 }Pseudosigma, 伪标准差1 t: w) W/ B& f" A( D; p( o2 ^
Purposive sampling, 有目的抽样
, y# e* V% b' r" y: A8 Z# bQR decomposition, QR分解
. E; r: C$ L7 p( v6 yQuadratic approximation, 二次近似7 B. @* n8 x# G. a
Qualitative classification, 属性分类+ U# t# o) W8 Q/ p
Qualitative method, 定性方法
) c! _: j1 O% `2 MQuantile-quantile plot, 分位数-分位数图/Q-Q图% \7 E. O; O0 w7 B; Y+ Q2 U E- S! c
Quantitative analysis, 定量分析
/ e! h, }! i8 A# [Quartile, 四分位数; W3 s5 p# ~# q/ s. V- L, c
Quick Cluster, 快速聚类
+ R" f- ]) k( {: ]( XRadix sort, 基数排序) L. _' a, F9 ~% p; G
Random allocation, 随机化分组
" H# [2 f3 T1 u3 p0 HRandom blocks design, 随机区组设计4 q- D7 w0 P, S' L& o% W* G0 f" Y
Random event, 随机事件( f& t9 a; T1 U2 ?2 |9 C
Randomization, 随机化
( B& w3 G3 ` W6 n' C6 E2 f$ f) O8 cRange, 极差/全距+ y* B* X8 d5 ~7 d1 p) y+ _
Rank correlation, 等级相关
, J9 N3 o5 X; s: T& ?. g9 [Rank sum test, 秩和检验: |8 K2 G( ~" O- _; A+ }. l! b/ S+ E0 c
Rank test, 秩检验; J8 z+ U7 V( I2 _
Ranked data, 等级资料
) a" O: Y6 w4 I, RRate, 比率
2 I+ u. V, Z! ` V7 ZRatio, 比例
' G4 w5 x) C8 VRaw data, 原始资料
; H$ d$ j# O8 l6 |* Y7 _. h7 I5 _. QRaw residual, 原始残差
$ \' k9 Z8 ~ _! p4 B- U. _Rayleigh's test, 雷氏检验
1 A8 g" ?* h# {% `7 p0 qRayleigh's Z, 雷氏Z值
/ D5 Z; [" C4 s+ S( UReciprocal, 倒数
9 g/ x6 k; W2 L9 O9 a; W1 ~' ]' rReciprocal transformation, 倒数变换
P# ]+ ?& m0 X% g/ GRecording, 记录
" M( l; h( Z0 B0 FRedescending estimators, 回降估计量
, g6 _& r4 u# Z& `) V2 k4 SReducing dimensions, 降维
z( ?# a; q; u$ K1 ^' z" E4 |Re-expression, 重新表达
9 ~4 _9 F4 M+ y! l* EReference set, 标准组9 `5 v( p1 h4 g- t% c& i
Region of acceptance, 接受域# b' J# n. W+ j6 _9 H! o
Regression coefficient, 回归系数# t$ n; y3 T; V5 V* `
Regression sum of square, 回归平方和- ?+ I5 Q. W5 s" p& J
Rejection point, 拒绝点
) P& y& v0 F$ h" s# s) K/ zRelative dispersion, 相对离散度" b# G8 v7 i8 Y6 x" D+ \1 }6 q+ @1 u
Relative number, 相对数
$ O+ ^5 g" c, F' o6 G4 w" H( [Reliability, 可靠性* z( X' m- E) F# V$ Y1 K
Reparametrization, 重新设置参数+ t' {2 W1 U; y0 H s
Replication, 重复7 v- M# ^. W7 V$ o, r6 C* o5 u) c
Report Summaries, 报告摘要
3 O. _3 V5 Z! N! c* T( X* ~* CResidual sum of square, 剩余平方和, t9 Q: f0 z$ ]1 D
Resistance, 耐抗性9 J( K3 H+ } e# Q1 s0 _
Resistant line, 耐抗线- T6 u- v; h$ ~1 w: F# t6 o9 [/ J
Resistant technique, 耐抗技术
3 z, Y b& @* h. X5 gR-estimator of location, 位置R估计量
$ q: L1 E, o* e8 Y9 BR-estimator of scale, 尺度R估计量2 s: U% u9 N' Q1 A# i. s
Retrospective study, 回顾性调查4 ^. X8 m/ a8 Q: @
Ridge trace, 岭迹
" K# S; v6 p1 JRidit analysis, Ridit分析" o+ |, D8 L9 A" [1 ?( \
Rotation, 旋转
0 |4 @$ J8 m2 IRounding, 舍入
7 I# L: D, L Z2 `$ w- [Row, 行
# v% b. M$ B* tRow effects, 行效应
: j- | G: ^0 G) qRow factor, 行因素
7 c& B: \" Y. L' z3 uRXC table, RXC表 m* A* q/ Q# \" ~& {0 q: S
Sample, 样本
1 Q* K9 @* O) L5 e5 i! x |8 [% }# b- MSample regression coefficient, 样本回归系数' l/ l3 m% F9 E! r5 ], z% j
Sample size, 样本量. }7 z; q; s% D) p2 O' V/ Y
Sample standard deviation, 样本标准差
8 r4 x0 Q1 x7 R0 l: o3 e1 uSampling error, 抽样误差
% z2 J4 X* Q3 `8 x1 ~- Q. F; l" xSAS(Statistical analysis system ), SAS统计软件包- s: b/ Y8 g# k5 Z2 M
Scale, 尺度/量表
# X0 N% }/ x. m! N" M; IScatter diagram, 散点图
x3 k+ @6 F1 A% U! I; O- cSchematic plot, 示意图/简图. u# B. o& {4 g4 W7 b5 H
Score test, 计分检验( ^. k4 z) |7 F
Screening, 筛检( g/ o$ `$ Z3 m& E( D
SEASON, 季节分析
$ h/ e% A/ x0 E# }+ YSecond derivative, 二阶导数
" L+ ]# p5 D* X% JSecond principal component, 第二主成分
9 h/ o0 B/ ?5 B1 @3 jSEM (Structural equation modeling), 结构化方程模型 ) @% f, A0 C, a7 q
Semi-logarithmic graph, 半对数图& v c1 j6 e6 @( }- J
Semi-logarithmic paper, 半对数格纸
% m4 J- X& c8 o; [4 r# @9 qSensitivity curve, 敏感度曲线
5 a# I/ n# M; T& kSequential analysis, 贯序分析1 k; D# ?3 M% R3 A+ O% F
Sequential data set, 顺序数据集
# j2 P1 [! e; e. `" L0 JSequential design, 贯序设计
5 u5 o/ a+ s! k6 P9 VSequential method, 贯序法9 B8 E8 f' F. j& G c+ {. z
Sequential test, 贯序检验法
, B& |$ n) I# b0 n' z& { }/ o5 sSerial tests, 系列试验
! H. C; [% V& C+ ]Short-cut method, 简捷法 + d4 v- S& J2 w9 U0 b+ S: m
Sigmoid curve, S形曲线 U- A V/ I& k
Sign function, 正负号函数
4 O& N3 o; W7 Z5 gSign test, 符号检验
, u; }' ]9 {7 @4 x+ GSigned rank, 符号秩0 L; H7 y8 _7 W) N
Significance test, 显著性检验; a7 e0 L! k9 b
Significant figure, 有效数字
0 O7 O f8 L- [, _3 l2 Y: HSimple cluster sampling, 简单整群抽样
' N q+ a( n* v* }3 OSimple correlation, 简单相关
; L$ p' N& L, ]* y- J5 DSimple random sampling, 简单随机抽样
9 F; Y% T. Z4 h" pSimple regression, 简单回归
& K: z H" G# s8 I# [ rsimple table, 简单表
r' O4 ~# y" c# P" ESine estimator, 正弦估计量7 G$ r: q2 ?+ y+ O* @
Single-valued estimate, 单值估计
( b0 g( s- V KSingular matrix, 奇异矩阵 W" R9 N' Q6 X1 [0 S
Skewed distribution, 偏斜分布$ k5 T0 ]) F2 U4 l' G. X6 a9 }
Skewness, 偏度8 F% L" r5 p! H% r+ u* b
Slash distribution, 斜线分布
8 F# N* G( H4 \& U# l8 Q0 HSlope, 斜率4 S; B- e* S& u3 ]) ^
Smirnov test, 斯米尔诺夫检验; h1 S8 i3 v# K4 w
Source of variation, 变异来源
' W2 i. s3 L. [! y' Q2 O6 J# KSpearman rank correlation, 斯皮尔曼等级相关
0 z7 @5 {# A' T0 HSpecific factor, 特殊因子
* d! n, s- B8 N9 v, h! CSpecific factor variance, 特殊因子方差0 l8 E0 n7 f. Z
Spectra , 频谱
# G; S% X9 F# OSpherical distribution, 球型正态分布
) C& n4 L- D! ?4 g0 hSpread, 展布
4 Y9 S8 a2 i# \8 N6 B, s7 B- cSPSS(Statistical package for the social science), SPSS统计软件包
8 r! |' R7 ?$ c; R5 H$ m/ gSpurious correlation, 假性相关- W. a0 \7 X0 T0 M7 m, e3 A5 G
Square root transformation, 平方根变换
; `: U' T; w$ w9 h; CStabilizing variance, 稳定方差
7 F b% L; |. X: X5 [3 E2 HStandard deviation, 标准差
2 p2 P" z" V& J4 q6 J1 }Standard error, 标准误
0 I0 }* R& q" [% d7 g! }Standard error of difference, 差别的标准误 J- {; C4 l9 k, T
Standard error of estimate, 标准估计误差2 R( x |- N! t# r; `, r/ }5 P/ y
Standard error of rate, 率的标准误
* F5 J" K$ C; c; o E# V$ x* CStandard normal distribution, 标准正态分布
+ ]. O* }! _8 B* |Standardization, 标准化& \/ \- \6 r- j" a7 T
Starting value, 起始值
' Y8 {3 ~, A# S8 q# IStatistic, 统计量$ C$ @8 U: i' y( k
Statistical control, 统计控制1 j1 U9 r5 [* V6 R# n" Y( J- ~
Statistical graph, 统计图& H6 t5 e; G+ k* ~* p
Statistical inference, 统计推断% v& G7 g+ h6 L. O
Statistical table, 统计表5 w* c4 E" E! f( T1 ~/ n
Steepest descent, 最速下降法) z1 J; Y6 r+ R& n
Stem and leaf display, 茎叶图$ O; T/ d' @; `) g, M0 C
Step factor, 步长因子
$ e- b7 C/ G: ~9 MStepwise regression, 逐步回归
& e8 E1 r- y6 c3 ?Storage, 存3 p4 r+ x# G$ U) [% G+ |
Strata, 层(复数)
. I' r3 ?- f' Y4 wStratified sampling, 分层抽样, E8 b/ `4 r U
Stratified sampling, 分层抽样& W4 U7 j/ m+ ^% M0 F9 q
Strength, 强度7 S7 R8 A# q0 p" }( a' o5 r! V
Stringency, 严密性8 k. ]6 N; \$ U8 j5 }- @# ?: h6 ?
Structural relationship, 结构关系4 `: ?/ L# P$ v. v( p# x/ }
Studentized residual, 学生化残差/t化残差; H: w6 x; t6 ]7 e
Sub-class numbers, 次级组含量
, p( }" v8 {+ j. d# c4 f# t& xSubdividing, 分割
$ _* P0 N" O0 ?Sufficient statistic, 充分统计量
3 e/ n0 A7 l) U7 B, l! X2 C ^Sum of products, 积和) V; a% v, u r8 k! ]) z
Sum of squares, 离差平方和
$ G3 \& Q9 J3 u( U& j; C+ s3 `/ [" DSum of squares about regression, 回归平方和& f8 n7 e( Y# o
Sum of squares between groups, 组间平方和* M+ F7 t5 W/ e, q x ?# o
Sum of squares of partial regression, 偏回归平方和
0 q0 ^$ _0 \3 ]1 [# {Sure event, 必然事件
9 ]5 [6 k; C2 y& aSurvey, 调查
5 } t0 w4 ^% q* D. b" `Survival, 生存分析
7 G, G) }, G& ?' jSurvival rate, 生存率
( b" n5 ?- x) |. P$ k2 x6 TSuspended root gram, 悬吊根图
. N9 w; C5 Z2 M& k, ]2 bSymmetry, 对称9 W" n; T: c6 Q2 n1 _
Systematic error, 系统误差" j- X% Q# Z3 ?. q9 Z
Systematic sampling, 系统抽样. U+ D# s& ~( ?' Q: u, N
Tags, 标签
4 B/ C+ C. J- ]% t' m9 n& |Tail area, 尾部面积
' ^( J" g& ^, z+ {5 C. w9 DTail length, 尾长
1 g2 H% ]$ X( s; F v! wTail weight, 尾重
! d! U$ _6 `$ H) W- G" WTangent line, 切线
3 K' t- u3 z! H' [' U- Y; ?Target distribution, 目标分布7 v( `% C3 _# m. w+ H4 n6 D; l
Taylor series, 泰勒级数# p6 d) C1 X' D* z! S# q+ y
Tendency of dispersion, 离散趋势+ v5 t7 k" P" d. f
Testing of hypotheses, 假设检验. D& M, |- z t7 [* L
Theoretical frequency, 理论频数0 V& w) m' R. n/ H2 X4 q4 k
Time series, 时间序列* q! C/ K5 {0 {5 n. W: z
Tolerance interval, 容忍区间. X4 {9 J1 {6 G+ y) O
Tolerance lower limit, 容忍下限
$ j2 e- |* ]$ S% y4 k, ]7 `; q* \Tolerance upper limit, 容忍上限" ?( D6 t2 H& V* o/ A9 R9 O# d
Torsion, 扰率
8 g5 z8 i) ~* Y0 y# _9 D2 ETotal sum of square, 总平方和
+ O( ^! F. d; }4 C, HTotal variation, 总变异
+ k; ~& \- ]+ r+ D8 a+ s+ t; |- UTransformation, 转换# E2 u# j; e$ q; V2 T$ h- A
Treatment, 处理
1 B3 I& W3 j1 ]: |Trend, 趋势
& W+ i5 b9 _; l- ~3 bTrend of percentage, 百分比趋势+ k4 w! e( O6 n! f
Trial, 试验
* f7 s6 W N, D- x. P |7 x0 ]Trial and error method, 试错法4 Q: ]8 D T6 e% ^
Tuning constant, 细调常数+ t# r; Z! m% ^: k# R5 ?
Two sided test, 双向检验+ ?3 K6 [8 Y. m0 K, R
Two-stage least squares, 二阶最小平方1 A/ ~, H* d( v
Two-stage sampling, 二阶段抽样; A+ |" v# W+ s5 I* l
Two-tailed test, 双侧检验$ F' Y" M# u/ D) r! _% k7 K0 z
Two-way analysis of variance, 双因素方差分析
7 e \. P& [' JTwo-way table, 双向表, o9 }* k/ W. L. h* Q8 M0 k E; j
Type I error, 一类错误/α错误7 \) X4 d' r( I. K% P2 ?
Type II error, 二类错误/β错误- q4 c" K" z7 ^3 y& l" I
UMVU, 方差一致最小无偏估计简称
0 o% S/ Z- s; }2 c9 _' H. G9 K7 KUnbiased estimate, 无偏估计
0 C {0 x5 D: ?# W; ?Unconstrained nonlinear regression , 无约束非线性回归, Z9 {! N v8 d$ y
Unequal subclass number, 不等次级组含量
q. j0 {0 z+ W8 p: PUngrouped data, 不分组资料
6 a" i; h4 x7 r) G5 F9 }4 pUniform coordinate, 均匀坐标
. U% w- X' G ^9 e$ v$ B7 HUniform distribution, 均匀分布
0 I9 H/ K" z+ {! @, C. A. j. {Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计, g. ?& e J9 P+ Z, }
Unit, 单元
G1 C8 P; [; {* }5 |0 a$ yUnordered categories, 无序分类8 J _* G- n% C' k% ~7 y2 N0 Z
Upper limit, 上限4 H) f$ A( U5 I3 l, q, W# ?
Upward rank, 升秩) W( a- m P1 z% r: {0 _9 O$ O
Vague concept, 模糊概念
3 s. }6 f t4 h4 J4 zValidity, 有效性
- s5 s( p! y# O0 r. |VARCOMP (Variance component estimation), 方差元素估计- D8 o0 e% `9 @" K9 b
Variability, 变异性 I/ r5 ]. B! v, ]4 l' o2 [: O
Variable, 变量
7 |+ o" T. }$ D/ j% }, C1 YVariance, 方差* `8 X5 ?' o) y% _6 h9 W
Variation, 变异
2 K0 | y: G3 A O* P( KVarimax orthogonal rotation, 方差最大正交旋转/ A- F9 _3 ^; O
Volume of distribution, 容积
- i0 y0 H$ B( X, FW test, W检验
. ]4 q0 X- Y L% _2 PWeibull distribution, 威布尔分布
) V* D( t) v6 m$ RWeight, 权数' _/ U5 L. F- O) d/ M
Weighted Chi-square test, 加权卡方检验/Cochran检验
) [' E& R* P4 z4 V- P( z7 pWeighted linear regression method, 加权直线回归7 u& _# P" k* W' u) \
Weighted mean, 加权平均数
' N5 v5 z W, P! U z9 pWeighted mean square, 加权平均方差7 }# {3 V& v" I+ H" L2 I% R/ e
Weighted sum of square, 加权平方和
7 x, E0 P: b* ]Weighting coefficient, 权重系数$ N0 |3 j! ?. h) O
Weighting method, 加权法
4 ?- N' B6 i- N& b- eW-estimation, W估计量- ~# X; S& \1 J8 Y9 @/ s
W-estimation of location, 位置W估计量
/ Q% \( `& j& J' G/ n. ?* eWidth, 宽度
" s. F9 l8 [5 H' ]5 ~4 |4 VWilcoxon paired test, 威斯康星配对法/配对符号秩和检验
% E3 M7 }; c5 A" y+ D4 rWild point, 野点/狂点8 F( y5 q, Z, d M* C# t- C
Wild value, 野值/狂值, s+ s8 [9 w. }0 d
Winsorized mean, 缩尾均值& v# B% V3 B& e, X% B
Withdraw, 失访
) T1 R& j8 a7 s9 uYouden's index, 尤登指数
! h0 N+ A& m: C6 V% qZ test, Z检验 ?- x1 Y6 {% s( a- I$ Z
Zero correlation, 零相关
1 K: g) j" Q- i$ F8 k6 MZ-transformation, Z变换 |
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